{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "year=2019\n",
    "month=9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import sys\n",
    "sys.path.append('../../py')\n",
    "import db\n",
    "import weighted\n",
    "import inspect\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.stats as stats\n",
    "import numpy as np\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_original=pd.read_sql(sql=f\"select * from _{year}{month:02} where monthly_salary>0 and monthly_salary<80000\", con=db.get_conn())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(90805, 94)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_original.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data_original"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "del data['publish_date']\n",
    "del data['published_on_weekend']\n",
    "del data['title']\n",
    "del data['company_title']\n",
    "del data['company_description']\n",
    "del data['job_description']\n",
    "del data['job_id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_sub_stats_by_prefix(data, prefix):\n",
    "    \n",
    "    features = [feature for feature in data.columns if feature.startswith(prefix)]\n",
    "    salary_mean=[]\n",
    "    salary_median=[]\n",
    "    salary_95_min=[]\n",
    "    salary_95_max=[]\n",
    "    count=[]\n",
    "    \n",
    "    features_out=[]\n",
    "    for feature in features:\n",
    "        #print(feature)\n",
    "        idata=data[data[feature]==1]\n",
    "        headcount=idata.headcount.sum()\n",
    "        values = idata.monthly_salary.values\n",
    "        weights = idata.headcount.values\n",
    "        #print(str(headcount))\n",
    "        if headcount==0:\n",
    "            continue\n",
    "        \n",
    "        salary_mean.append(weighted.weighted_mean(values, weights))\n",
    "        q = weighted.weighted_quantile(values,[0.025,0.5,0.975],weights)\n",
    "        salary_median.append(q[1])\n",
    "        salary_95_min.append(q[0])\n",
    "        salary_95_max.append(q[2])\n",
    "        count.append(idata.headcount.sum())\n",
    "        features_out.append(feature)\n",
    "    sub_data=pd.DataFrame()\n",
    "    sub_data['rank']=range(0,len(features_out))\n",
    "    sub_data[prefix]=[f.replace(prefix,'') for f in features_out]\n",
    "    sub_data['salary_mean']=salary_mean\n",
    "    sub_data['salary_median']=salary_median\n",
    "    sub_data['salary_95_min']=salary_95_min\n",
    "    sub_data['salary_95_max']=salary_95_max\n",
    "    sub_data['head_count']=count\n",
    "    sub_data['percentage']=count/np.sum(count)\n",
    "    sub_data=sub_data.sort_values(by='salary_mean', ascending=False)\n",
    "    sub_data['rank']=range(1,len(features_out)+1)\n",
    "    #sub_data=sub_data.reset_index()\n",
    "    return sub_data\n",
    "\n",
    "def apply_style(sub_data):\n",
    "    return sub_data.style.hide_index().format(\n",
    "        {\"percentage\":\"{:.2%}\",\"salary_mean\":\"{:.0f}\",\"salary_median\":\"{:.0f}\",\"salary_95_min\":\"{:.0f}\",\"salary_95_max\":\"{:.0f}\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_pl=get_sub_stats_by_prefix(data,'pl_')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"col_heading level0 col0\" >rank</th> \n",
       "        <th class=\"col_heading level0 col1\" >pl_</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col3\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col4\" >salary_95_min</th> \n",
       "        <th class=\"col_heading level0 col5\" >salary_95_max</th> \n",
       "        <th class=\"col_heading level0 col6\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col7\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow0_col0\" class=\"data row0 col0\" >1</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow0_col1\" class=\"data row0 col1\" >haskell</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow0_col2\" class=\"data row0 col2\" >22159</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow0_col3\" class=\"data row0 col3\" >19778</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow0_col4\" class=\"data row0 col4\" >7500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow0_col5\" class=\"data row0 col5\" >45000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow0_col6\" class=\"data row0 col6\" >66</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow0_col7\" class=\"data row0 col7\" >0.02%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow1_col0\" class=\"data row1 col0\" >2</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow1_col1\" class=\"data row1 col1\" >rust</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow1_col2\" class=\"data row1 col2\" >19868</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow1_col3\" class=\"data row1 col3\" >16984</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow1_col4\" class=\"data row1 col4\" >5000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow1_col5\" class=\"data row1 col5\" >50333</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow1_col6\" class=\"data row1 col6\" >376</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow1_col7\" class=\"data row1 col7\" >0.09%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow2_col0\" class=\"data row2 col0\" >3</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow2_col1\" class=\"data row2 col1\" >julia</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow2_col2\" class=\"data row2 col2\" >18875</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow2_col3\" class=\"data row2 col3\" >21500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow2_col4\" class=\"data row2 col4\" >2500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow2_col5\" class=\"data row2 col5\" >30000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow2_col6\" class=\"data row2 col6\" >4</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow2_col7\" class=\"data row2 col7\" >0.00%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow3_col0\" class=\"data row3 col0\" >4</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow3_col1\" class=\"data row3 col1\" >lua</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow3_col2\" class=\"data row3 col2\" >18011</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow3_col3\" class=\"data row3 col3\" >16500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow3_col4\" class=\"data row3 col4\" >5000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow3_col5\" class=\"data row3 col5\" >35000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow3_col6\" class=\"data row3 col6\" >3247</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow3_col7\" class=\"data row3 col7\" >0.81%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow4_col0\" class=\"data row4 col0\" >5</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow4_col1\" class=\"data row4 col1\" >matlab</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow4_col2\" class=\"data row4 col2\" >17834</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow4_col3\" class=\"data row4 col3\" >17500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow4_col4\" class=\"data row4 col4\" >5250</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow4_col5\" class=\"data row4 col5\" >37500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow4_col6\" class=\"data row4 col6\" >5680</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow4_col7\" class=\"data row4 col7\" >1.41%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow5_col0\" class=\"data row5 col0\" >6</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow5_col1\" class=\"data row5 col1\" >python</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow5_col2\" class=\"data row5 col2\" >17801</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow5_col3\" class=\"data row5 col3\" >15000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow5_col4\" class=\"data row5 col4\" >4000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow5_col5\" class=\"data row5 col5\" >41666</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow5_col6\" class=\"data row5 col6\" >30692</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow5_col7\" class=\"data row5 col7\" >7.63%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow6_col0\" class=\"data row6 col0\" >7</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow6_col1\" class=\"data row6 col1\" >go</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow6_col2\" class=\"data row6 col2\" >17698</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow6_col3\" class=\"data row6 col3\" >15000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow6_col4\" class=\"data row6 col4\" >5500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow6_col5\" class=\"data row6 col5\" >37500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow6_col6\" class=\"data row6 col6\" >29663</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow6_col7\" class=\"data row6 col7\" >7.37%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow7_col0\" class=\"data row7 col0\" >8</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow7_col1\" class=\"data row7 col1\" >perl</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow7_col2\" class=\"data row7 col2\" >16358</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow7_col3\" class=\"data row7 col3\" >14000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow7_col4\" class=\"data row7 col4\" >4577</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow7_col5\" class=\"data row7 col5\" >37500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow7_col6\" class=\"data row7 col6\" >2655</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow7_col7\" class=\"data row7 col7\" >0.66%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow8_col0\" class=\"data row8 col0\" >9</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow8_col1\" class=\"data row8 col1\" >ruby</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow8_col2\" class=\"data row8 col2\" >16119</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow8_col3\" class=\"data row8 col3\" >15000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow8_col4\" class=\"data row8 col4\" >2500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow8_col5\" class=\"data row8 col5\" >33016</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow8_col6\" class=\"data row8 col6\" >1334</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow8_col7\" class=\"data row8 col7\" >0.33%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow9_col0\" class=\"data row9 col0\" >10</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow9_col1\" class=\"data row9 col1\" >kotlin</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow9_col2\" class=\"data row9 col2\" >15911</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow9_col3\" class=\"data row9 col3\" >14000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow9_col4\" class=\"data row9 col4\" >6000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow9_col5\" class=\"data row9 col5\" >30000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow9_col6\" class=\"data row9 col6\" >1187</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow9_col7\" class=\"data row9 col7\" >0.30%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow10_col0\" class=\"data row10 col0\" >11</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow10_col1\" class=\"data row10 col1\" >cpp</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow10_col2\" class=\"data row10 col2\" >15383</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow10_col3\" class=\"data row10 col3\" >12500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow10_col4\" class=\"data row10 col4\" >3750</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow10_col5\" class=\"data row10 col5\" >37500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow10_col6\" class=\"data row10 col6\" >64161</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow10_col7\" class=\"data row10 col7\" >15.95%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow11_col0\" class=\"data row11 col0\" >12</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow11_col1\" class=\"data row11 col1\" >swift</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow11_col2\" class=\"data row11 col2\" >14972</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow11_col3\" class=\"data row11 col3\" >12500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow11_col4\" class=\"data row11 col4\" >5000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow11_col5\" class=\"data row11 col5\" >33750</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow11_col6\" class=\"data row11 col6\" >3320</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow11_col7\" class=\"data row11 col7\" >0.83%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow12_col0\" class=\"data row12 col0\" >13</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow12_col1\" class=\"data row12 col1\" >objective_c</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow12_col2\" class=\"data row12 col2\" >13798</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow12_col3\" class=\"data row12 col3\" >12500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow12_col4\" class=\"data row12 col4\" >5250</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow12_col5\" class=\"data row12 col5\" >22875</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow12_col6\" class=\"data row12 col6\" >374</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow12_col7\" class=\"data row12 col7\" >0.09%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow13_col0\" class=\"data row13 col0\" >14</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow13_col1\" class=\"data row13 col1\" >typescript</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow13_col2\" class=\"data row13 col2\" >13686</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow13_col3\" class=\"data row13 col3\" >12500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow13_col4\" class=\"data row13 col4\" >5762</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow13_col5\" class=\"data row13 col5\" >29166</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow13_col6\" class=\"data row13 col6\" >984</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow13_col7\" class=\"data row13 col7\" >0.24%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow14_col0\" class=\"data row14 col0\" >15</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow14_col1\" class=\"data row14 col1\" >java</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow14_col2\" class=\"data row14 col2\" >13393</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow14_col3\" class=\"data row14 col3\" >12500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow14_col4\" class=\"data row14 col4\" >3750</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow14_col5\" class=\"data row14 col5\" >31500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow14_col6\" class=\"data row14 col6\" >135643</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow14_col7\" class=\"data row14 col7\" >33.71%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow15_col0\" class=\"data row15 col0\" >16</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow15_col1\" class=\"data row15 col1\" >php</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow15_col2\" class=\"data row15 col2\" >12996</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow15_col3\" class=\"data row15 col3\" >11500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow15_col4\" class=\"data row15 col4\" >3750</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow15_col5\" class=\"data row15 col5\" >35000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow15_col6\" class=\"data row15 col6\" >18758</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow15_col7\" class=\"data row15 col7\" >4.66%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow16_col0\" class=\"data row16 col0\" >17</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow16_col1\" class=\"data row16 col1\" >javascript</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow16_col2\" class=\"data row16 col2\" >11610</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow16_col3\" class=\"data row16 col3\" >11000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow16_col4\" class=\"data row16 col4\" >4000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow16_col5\" class=\"data row16 col5\" >24000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow16_col6\" class=\"data row16 col6\" >51108</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow16_col7\" class=\"data row16 col7\" >12.70%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow17_col0\" class=\"data row17 col0\" >18</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow17_col1\" class=\"data row17 col1\" >c_sharp</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow17_col2\" class=\"data row17 col2\" >11304</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow17_col3\" class=\"data row17 col3\" >10416</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow17_col4\" class=\"data row17 col4\" >3750</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow17_col5\" class=\"data row17 col5\" >25000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow17_col6\" class=\"data row17 col6\" >51189</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow17_col7\" class=\"data row17 col7\" >12.72%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow18_col0\" class=\"data row18 col0\" >19</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow18_col1\" class=\"data row18 col1\" >vba</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow18_col2\" class=\"data row18 col2\" >10961</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow18_col3\" class=\"data row18 col3\" >10500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow18_col4\" class=\"data row18 col4\" >2772</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow18_col5\" class=\"data row18 col5\" >25000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow18_col6\" class=\"data row18 col6\" >467</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow18_col7\" class=\"data row18 col7\" >0.12%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow19_col0\" class=\"data row19 col0\" >20</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow19_col1\" class=\"data row19 col1\" >delphi</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow19_col2\" class=\"data row19 col2\" >10805</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow19_col3\" class=\"data row19 col3\" >10000</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow19_col4\" class=\"data row19 col4\" >3750</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow19_col5\" class=\"data row19 col5\" >22500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow19_col6\" class=\"data row19 col6\" >1375</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow19_col7\" class=\"data row19 col7\" >0.34%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow20_col0\" class=\"data row20 col0\" >21</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow20_col1\" class=\"data row20 col1\" >visual_basic</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow20_col2\" class=\"data row20 col2\" >10649</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow20_col3\" class=\"data row20 col3\" >10472</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow20_col4\" class=\"data row20 col4\" >4500</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow20_col5\" class=\"data row20 col5\" >21917</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow20_col6\" class=\"data row20 col6\" >48</td> \n",
       "        <td id=\"T_d6a82c7a_d892_11e9_9a68_701ce71031efrow20_col7\" class=\"data row20 col7\" >0.01%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x21fbcd7dcf8>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "apply_style(data_pl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"col_heading level0 col0\" >rank</th> \n",
       "        <th class=\"col_heading level0 col1\" >pl_</th> \n",
       "        <th class=\"col_heading level0 col2\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow0_col0\" class=\"data row0 col0\" >1</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow0_col1\" class=\"data row0 col1\" >java</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow0_col2\" class=\"data row0 col2\" >33.71%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow1_col0\" class=\"data row1 col0\" >2</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow1_col1\" class=\"data row1 col1\" >cpp</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow1_col2\" class=\"data row1 col2\" >15.95%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow2_col0\" class=\"data row2 col0\" >3</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow2_col1\" class=\"data row2 col1\" >c_sharp</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow2_col2\" class=\"data row2 col2\" >12.72%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow3_col0\" class=\"data row3 col0\" >4</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow3_col1\" class=\"data row3 col1\" >javascript</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow3_col2\" class=\"data row3 col2\" >12.70%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow4_col0\" class=\"data row4 col0\" >5</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow4_col1\" class=\"data row4 col1\" >python</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow4_col2\" class=\"data row4 col2\" >7.63%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow5_col0\" class=\"data row5 col0\" >6</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow5_col1\" class=\"data row5 col1\" >go</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow5_col2\" class=\"data row5 col2\" >7.37%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow6_col0\" class=\"data row6 col0\" >7</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow6_col1\" class=\"data row6 col1\" >php</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow6_col2\" class=\"data row6 col2\" >4.66%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow7_col0\" class=\"data row7 col0\" >8</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow7_col1\" class=\"data row7 col1\" >matlab</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow7_col2\" class=\"data row7 col2\" >1.41%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow8_col0\" class=\"data row8 col0\" >9</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow8_col1\" class=\"data row8 col1\" >swift</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow8_col2\" class=\"data row8 col2\" >0.83%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow9_col0\" class=\"data row9 col0\" >10</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow9_col1\" class=\"data row9 col1\" >lua</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow9_col2\" class=\"data row9 col2\" >0.81%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow10_col0\" class=\"data row10 col0\" >11</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow10_col1\" class=\"data row10 col1\" >perl</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow10_col2\" class=\"data row10 col2\" >0.66%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow11_col0\" class=\"data row11 col0\" >12</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow11_col1\" class=\"data row11 col1\" >delphi</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow11_col2\" class=\"data row11 col2\" >0.34%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow12_col0\" class=\"data row12 col0\" >13</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow12_col1\" class=\"data row12 col1\" >ruby</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow12_col2\" class=\"data row12 col2\" >0.33%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow13_col0\" class=\"data row13 col0\" >14</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow13_col1\" class=\"data row13 col1\" >kotlin</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow13_col2\" class=\"data row13 col2\" >0.30%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow14_col0\" class=\"data row14 col0\" >15</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow14_col1\" class=\"data row14 col1\" >typescript</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow14_col2\" class=\"data row14 col2\" >0.24%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow15_col0\" class=\"data row15 col0\" >16</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow15_col1\" class=\"data row15 col1\" >vba</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow15_col2\" class=\"data row15 col2\" >0.12%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow16_col0\" class=\"data row16 col0\" >17</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow16_col1\" class=\"data row16 col1\" >rust</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow16_col2\" class=\"data row16 col2\" >0.09%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow17_col0\" class=\"data row17 col0\" >18</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow17_col1\" class=\"data row17 col1\" >objective_c</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow17_col2\" class=\"data row17 col2\" >0.09%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow18_col0\" class=\"data row18 col0\" >19</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow18_col1\" class=\"data row18 col1\" >haskell</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow18_col2\" class=\"data row18 col2\" >0.02%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow19_col0\" class=\"data row19 col0\" >20</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow19_col1\" class=\"data row19 col1\" >visual_basic</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow19_col2\" class=\"data row19 col2\" >0.01%</td> \n",
       "    </tr>    <tr> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow20_col0\" class=\"data row20 col0\" >21</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow20_col1\" class=\"data row20 col1\" >julia</td> \n",
       "        <td id=\"T_d73fdb2c_d892_11e9_ba6d_701ce71031efrow20_col2\" class=\"data row20 col2\" >0.00%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x21fb6cb32b0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_pl=data_pl[['pl_','percentage']].sort_values(by='percentage', ascending=False)\n",
    "data_pl['rank']=range(1,22)\n",
    "data_pl=data_pl[['rank','pl_','percentage']]\n",
    "#data_pl.style.format({\"percentage\":\"{:.2%}\"})\n",
    "data_pl.style.hide_index().format({\"percentage\":\"{:.2%}\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_pl=data_pl.sort_values(by='percentage')\n",
    "\n",
    "# Pie chart, where the slices will be ordered and plotted counter-clockwise:\n",
    "labels = data_pl['pl_']\n",
    "sizes = data_pl['percentage']\n",
    "#explode = (0, 0.1, 0, 0)  # only \"explode\" the 2nd slice (i.e. 'Hogs')\n",
    "\n",
    "fig1, ax1 = plt.subplots(figsize=(15, 9))\n",
    "ax1.pie(sizes, labels=labels, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "ax1.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "plt.title(\"Programming Languages in China, March 2019\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Word Cloud"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from wordcloud import WordCloud\n",
    "wc=WordCloud()\n",
    "wc_dict = {}\n",
    "for index, row in data_pl.iterrows():\n",
    "    wc_dict[row['pl_']]=row['percentage']\n",
    "\n",
    "\n",
    "wc=wc.generate_from_frequencies(wc_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "wc_dict['c語言']=0.33\n",
    "wc=wc.generate_from_frequencies(wc_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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S4x1BfcrI/mTk6JZ+P7KyudqgnYEmNIXkeJbkWHZf5rUZA189RO7iwoYRpGpEpfeLw+hxA9/1qS9Wg6o2ISHbIBS4lxS9I0H3d94h8fr4ulBzVTOJjvdi9KRRIhpLhSru6v7Ulls5P0/u4gLdrw9gZCyO/63XUE2N3MV5WqvrS1IJRaAnDaI9cXzb27fE3+ypboyUSflOkfpiZcNgi6DYcudauSpwGw71xf25ho1c/b4llDrcgZmxHqvCr2gKHa/0cuQ7pw/EXmffO8PkLi4w9+PJdSInNIXuNwYZ/fYxAJyazcLP726ZShESco9Q4F5ChK5iHekjfnasbR6VGjeJnRomenSK8kc392VeTs3m+u9+Frj0RjNkT/Vw8u8a5C7MU50r41RtpCdRDZVIysTqimFkLPKXFvdN4LrPDTDwlTHK00Vqs2UauRp2pYVvewhFoMUixAeSdL3WT3wwhVO3KVxdpnx3f+aXuzCPXTmNFtNJjmY4/rfOsfSL2WDfaq3nWmI0Q/frA2SOdZK/skTHqZ59mdtGNFaqqKbOsb9xluRohtJkAadqo+oK8aEUfe+OkhzJ4NkehStLzP148pnNNeT5IxS4lxDF0LHG+1C0zStX6Jk4xlAn7JPAIWHls3mu/pNfcOgvnaTzlV5Sh7IkRzNBY9PaA4HTYxFUQ8OptqjO7mNzRRFYRunjXUhP0io2cCo2nrMmcFEdMxtFNVTcusPC+3eZ+qNruLX9sTpKt/Lc/d4Nxr9zmkjSYOzXj9P5ai+tUhNkENQR7Y3jNVwmv3uVymyJ7MnufZnbRtQWKuQuLDD89SMc+auvUF+p4dZsFF0l2h1Hi+r4jkfu0gI3/8WlsCdcyI4IBe4lRKgKenrrahCKqaPFt1efcLeQnmTux5M0czW6Xx8ge6qH2EASMxvFzEYRAjzbW+sqXaN0K8/Kp3P7Nr+lT+YwO2NB8nR3nEjKIJIyUVQF6fu4DZfGUoXKdIn8lSWWPprZ16osvusz+d2r2DWbvreGgjy3wRTxoTRe06W12mDlF3MsfDjNws/vYqTMDTsS7BdCVbjz769TmS7S9+4omaOdxAdTKLoalAS7tkr+80Xm/vwOuYvPR+5VyMEhFLiXEAm0jT54+Di5veN2G+lJchcXKd7MkxhJY3XHiCRNlEgQHeg7XtCVerVBfbFCY3n/nupXry3TWKkR609gZqPosQiKoQbJx77Ea3nYpSa1pQq1ufKm+0VOtcXsjyepzpbxbHdbnQfmfjRJeaqAoqnkLi5sWP2kWagz9d0rFD5fJNafRE8YCCHwbBe73KI2V6J8ZxXpSfyWx6V/9AFCUyhcbT9+Y6XG1B9eY/kXc9ilJsUddAvYDM3UcKo2038yweqNHInhNJHkWufxpktjpUZ5qkAzt3lfuZCQjQgF7mXE9XDyW6cA+A0bt/zsco7chsPq9RVWr2/dT20/aeZqNHO7UGi44ZI7v0Du/MK2f2fl/Dwr57e2ZLyWR+Hq8qaiBcG+593vb+2CtotNFn6++61QhKqAEEhfUp4sUJ48+OWfQp4fwm4CLyF+y6V+cx5/i3qCTr5C8872+5mFhISEHCRCC+4lRLoejcklSh9cJ/3lUxtGUrrlOtWLU9RvPT/7HnoiQt8XR+h+Y2BXzzv53aus3lh5vpLOQ0JCQoF7WXFXq6z8wYe4qzUSr42hd6cRuopft2nN5ih/coviz6/hVZ5dAMJO0Uyd7KluRr99fFfPu/TxLMWJXChwISHPGaHAvaRIz6cxtYRbrFH68AZq3EQoCtLxcMs1WotFvNLztbHvNhxylxa3TH/YKdXZ0u5Vzw8JCdk3QoF7mfElTr6yrYCT5wG37rD0yey2ohF3QqvYCK23kJDnkFDgQl4YpC9xyi2cLXqvhYSEvByIZ90uA0AI8ewnERISsi/oiQip8Q5UQwtSQa4u47sHu8FtyLNBSvlU3W1DgQsJCQkJOZA8rcCFeXAhISEhIS8kocCFhISEhLyQhEEmISEhISF7Sqw/SWwwiVO1EYqgPFkgNpAiNZ7Fs11qcxVUU6NwZYnsyW7yl5dgF1JzQgsuJCQkJGRPMTujeA2X2lwZsyOKamrEB1MY2SjF6zmS41mMlEn6SCdGxuKpNt4eIhS4kJCQkJA9RSgKTt3Grdt4LY/OM31EexOoEZXMyW6EEOQvLzH8zaOsXlvZtcIKoYsyJCQkJGRPKVwNXI6+65M7P4+iKaCs2WlSIn1JJGVQnSnRKu5eB5MwTSDkuUVENIzeDOZoF0Z/Fr0njZ6JoyWjKGYEoSuAQLoevu3g11u45QZOoYK9WKQ1W1grV1bdFX9/yO6id6ewxnow+rNE+jLoHXG0ZAwlaqDoQQ8+3/WRjovfaOFWmjirVZylIq35VRp3lrCXinBAcuwEAl2xMLU4EcVCUwwUoSIQSCS+9PB8G9tv0PRq2F4dycGY+35gdcdwGw5Oxb7/szAP7iUi87VX6Pz1N9GziX0bs/TBDRZ+50f49QNQHURViHSnSLw6RuyVEazxHrSEhVBVUBWEqgSNRxUBj3ZIkBJkUO0E30d6a1+Oh71QoHLhDqUPr9OaySNdb9enbo330v/3fgWjP9v2mNr1WVb+4APqN55RBwdFEH91lKH/8teCPm1tKH8ywfLv/Rx7ubSrw6sJi/iZUeKvjhI7MYiWiQdrqikIRQnWWKyt7cPLu9aYV8p7ayuDtXU93HyF6pVpyh/dpH5jHr9ptxt+11GESirSS9YcJBXpIaZn0JQIguDBK/iIPvJGJMhA7nB9h7pbpGwvUWjOU7IXcf0D8He4V6w1DX6YpxW40EX5HKEYEbR0HL1j/wROTZiPi8V+IkDPxEm9c5zkW0exDvcidA2hqcHNb7tzWztOqAAPFWOWEi0VxTrcR+evv0H18jS5f/cR9Rvzuyp0brlBczZP/JWRtsfETw9TvTD1zAROS0ZJvHYIvSvZ9rr6TRunUMXOlXdlTMXUSbw+TuqdE8TPjKAYOkJXEepal/TtsCYUwdGPrG3SwhjqJPO1MzTvLJH//nnKn0zg1/ZKKARRLcVA/BQ90XEMNYaCgliz1Lb9eQUiisTSkmSNQYYTZ7G9OrnGXeZq16jYKy+edbcHXpRQ4EIOJqpC9HAfHd94jcSbR1BjkQc3vd0UXCEQqgjEMqKReusoiTOjFH54ieXf+zlu8ek7dwM4hQq1S3fI/vIZlMjGf3ZqMop1qBctG8ctVHdl3J2gpQKB2+wm3JzNU5+Yf+qbUaQvQ/Zrr5D+ymm0bDzoAKEqa1q1S+srAkEREQWhq8RODGGN91E5P8nKv/459Yntd1LfDoYa5VDqTfqix+9bajsRtEcRQgSyLRRUNDQRYSiRpC92nJXGJHfKn1F18khCB1g7QoELOVgIgXW4l96/+VXip0cCV5mysyffJx9agCpQYgad33oda6yHmX/4x9gLq7S9hwiB3t2Fmkrh5nK4hdWNj/N8WvMF6jfniZ8ebju+Od6LOdpNdZ8FTugqxnAn5kj3pse1pnM0bj65han3pOj+K++Qfvc4asyENVfoXq/v/bU1dVJvHcXoz7L4uz+m/MnELlgOgm5rjBPZr2Ko8R1batseRQgEKrqi0Bc7Toc5xO3SJyzUbuDKF9h1+RSEaQIhBw9FkHh1DCWi7cwNuUsIIRCaSuz0MCP/zV9C70pufKCqkv7WN8j+1l8h/uY5Ov7aXyXxpXfbntdeLlG9eIfN9r2tkW6s0Z77N/79QktGSb5+eFO3oFOoUJ+Yx32aPoG+JHZyCDUZDdzMYn8eXu4hRGCtmyNd9P2nXyP5+vhTWYwCwVjyDc52fRtTTaCIvf+8CiFQhIKhxjmR/QqH029jqLE9HfN5JRS45wjp+0jbxW85+Lb74Mu59+Uh3bUvz3sQSOHf+wo24u99HUikpDWdo/LZ7R3+2tr7ejiAxH34eqxdgx28byEE1rF++v7mL6HGzcdfVwTGyBBL//D/JPfP/xW5f/4vMcbH2p7PqzSo35zDXW1vnYmIinW4F6Mvs+157gZaOkri9fG2r0spac7kqF2ffapxnJUylc9u4ze2H+zxYG3lrq6tMdhB5196m+iRvid5K7AmbkfT7yC2ELYHf3c+vvTxpbfJl4+U/pZ/p8HDgcJI4iyHkm+GIrcBoYvyOaLwZxco/uQKihVBNSMoVgTFMlAsHcWMoFrBz1TLQDH1tf9eO85c+/nasYoZQRgaSkTf/mb+PuHbLrnvfUri9fEgem4D5L2oSM+/HxXplRu05vM4uQpetYlbbSJdD9WKoCYsjL4MxkjXWuTlQ1F5myCEIPPVVyh9cIPSRzfBCzb2g0AXDbdURhgR8HyEpuGVNg++sJeKVC9Pk/nSyQ0tByEE1uE+zJEuWrP5bV6xp0OxIsRODKFn4m2Pka5H8+4Kzamnbya7+sPPSb19DMWKbHj979/U7z+gSfymTWsuj71Uwqs28WpN/IaNYmioCYtIZwpztButIx7s1WrbW9vEmVHqbx6htbiKV95Z/lW3Ncbh9BfbjiOlvB8R6UsP26tTd4vUnRItr44nHTzfwcdHEQqq0FEVHUOJEtVSWHoaQ7VQpBYI6Aauz2CPDkaSZ2l6FWYqn+PK/YsUPeiEAvc84Uv8ho3fsHF34XTmWDeH/vvfRu9o44J7Vng+9etz1K/PETs5dP/HQRi4DPLaWg72UpHKxTvUrs7QvLOMkytvuZ+imDrRowNkfuVVEq+OoqViW+/xCej+zjtUL9+9fxPMfucvI1QFNZmi97/4z3GLRdR0itbtqU3Ht5dL1C5Pk373eJDesAFGXwZztIfKp5P7EtauJiwSbx7Z9Bh7sUj9xtyuRJY27ywHIp9NIEz9/s/l2tpK18Mt1qlcnKT6+TTNO0u05gr3Hy7aITQVY6iD9FdOk37nOHpXamuhE5D68kmqV6apXth87R4mokQ5kf2l+7GbDxMIm4/jNyk058k1pig0Z2l4O488NdU4GXOATnOUjDGAoUVRUDd8T4eSb1JsLVFszYWBJ2uEAvcy48n2wRPPGL9pk//+eaLHBkARSMfDq7dozeQof3STyoUpmtMrOw4Q8JsO1Ut3qF66Q/zVUbp/6z1ixwdB3/imcY/o0X6iR/qpnJ8EX1L9+QcPvfogL0s6zqbjS9ulOb1C484K0fHeDY8RQhA90ocx2EHj1u5G+m0wGJGOBLFTQ20PkVLSms1Tu/Z07smHWf2PF0mcHUU3UuD5wQPLSpnyJxNUfnErcIV6O1tb6Xo0p5ZZnPohqz+4RPdffpvUeydRTH3TtTUHOoge7adxawGv2tzWWGPJcxhq9LHzSilx/CbLjUnuVi5QsVd29B4epelVWajdYKF2g5iWZTB+ip7oYSwtgRDrvRu6ajKUeIW6u0rL253o3+edUOBCDiTS8aicv03j9iJqzKRyYZLVH1+hfmN21/JlqhfvYC+X6PvP/gLJ18cRbcL375F65zjVz+8ibZfW9AwAwjJRDGPtZiORzta2tb2wSu3yNNahnrY3Xmu8F3O4k8btxSBJfY9QYwaJ18dRzUjbY7xqk8bUIs4uJnbXrs5Quz5HDEHj1jyFH12h8osJpLM7uYetmRwL/++PsPNVun7jTdSosenxsZNDlD+e2JbAacKgN3Z0LWH7AVJKml6V26WPmK1efqr5b0TNLXCj+FNWW/McSr1JMtKFItZ7AbqtMe6Wz9Py6hzYp9d9JBS4kAOLV2kw87/+MV65jrNHYfP2wiorv/8BeiZG9Gh/2z0/gPirYwhdRdprIqaqpL/5dYyxUbRMCr/WwJ6bI/e7/2LTMZ1ClfrNObzaK2hxa8Nj9Ewc61Avlc8mdy0XbyPUuEXijcPtD5ASe6FA7crMro+99C9+grQ97JXSniT5usUaqz+8RKQzQearpxHaxi5hIMg/zMThztZ7jJ3WCLpirns4CSy3BjdXf8ZC/cauzL8dy43beNLhaPodkpHudZacpkToMIeoOgW8cC8ujKIMObhI1w/21vY4J6x+fZbS+ze2DH83etLoqQeRakIRRPp6WPo//jH1zy6y/I//KV5xG1bOmsuvfn1u08OixwYwBju29R6eBKEpGEMdWIc2dpVCEMTTms3velI0QGsmH9SK3MM6oPZ8gdIOOdagAAAgAElEQVT712nO5DY9Ts/E0bPxTUXwHmmj/zHLSeKzVL+95+J2j3xzmoXazTVL7dH59aGK0HaBUOBCQgAof3QDe7G4eai5AHO466Eq6OA3m4ELUVVRLBMlHt3WePbiKvVrs5sGbVhj3ZhDnQhtb/5MFcsg+YWjW+S+ValdnzsYtUifkPrEArWrM0h/kyAVAZHuNEq0vav2HnE9w8M1JKWUuL7N3cr5XZjt9llsTFBzVx/7zEb19GMC/LISCtxTIdCsBGamF0Xf3McfcrBpzRVoTq8gW5sHiejdKe7d3KSUtKbuIgCvViP+3hfxa9sLNfdqLRqTS5sWLFbMCNGj/eidqe2+jR2hpaJBonMbpJS0FgrUrkzvyfj7hbtapTm1vGUagJaOoRj6psdAENn4aPRkzS1QdQpPNc+d0nQrVO08nlz/mTXU2GMBKC8r4VXYBDViEUlk21Y6UDSNrpPvcPjbf594b/sE35Dng+adZbwtLBUtE3vw8O55lH/0E/xmk/IPf0z1/Y8o/ccfbX+8uSAycTOrMXpsAGOgfQeCJ0VENKLHBoh0txdPv+kEuW9buPeeB+yVEvbK5mH6atxE6Fu79lRl/TESSdl+Nteo7pZw/fV7barQNkxfeBkJBW4TksMn6HvjV1G0rd0WIc8/rfnClhU2FDOy4fOObNk48wtondsXI2e5RP3mPH6jvdVoDHRgjnSjWLv7GVTMCKkvHtt8fislqp/ffSF65TmrVZzVyqbHKIa2raIHjz+PSOwN9sL2A8dv4vOIm/v5X65dIxS4TUgMHEWPpZ5tu5iQfcOrNLZMZA46AQjUTPqxL723h/hbX9j2eEF1kGWad5faHiNUhdiJwU0trR0jBJHOxKate+S94tBPWZrroBAUSNjc/Sw0ddMo2ntsVCnEl7vfQ3B7PK5mrrTDRO81nrtQG6FqGIkOhKrSKheIxFKoZgwhBG6rjlMt4tkPfO1GshMtmqBVyuE2Hn+CM9I96FacRn4ez26gWXH0aArVsIj1jCJ9n0TfYXw3+FBL6VOdv/X4xBSVSLID3UoiFBXfs3HrFexaCeT6zW2h6uixFLoVR6ga0nNxGhWcWhnpPfgjVI0oRrITp1ZESh89lkLVTaSUeHYDu5LHd8JQ4N3Ca9hB6a9NuHcDTH31y3iV9Z8nYUTQMukdjdmay1O/MU/06EDbJqPRI30Y/dnAVbgL1pSIqCTOHQqq+bfBqzRoTCzgrr4YCcO+7T5I72hD0Ipp63M13DJxveMhN6AgorS/lnuJphgorA8oaXpV5DMT3IPFcydwupWk+9Vfwkh2Urj5MYnBYxipbhQ9glMrsXr7PKWpz3GbVRAK6UOv0nH8bZYu/IDCzU+Q/oOFVzSdvtd/hWjXCHd++M+oL98l2jVEeuxVzHRPsP8mffq+8C1Yi8DyfY+b3/1f1vkphKJiZfvIjL2CmQ4CTnzPob4yQ+7aBzRyD56C1YhJvO8w6fGzWJkehKrhey7NwiLFyQtU5m/jO0GyabRrkP43v0155jpSesR7xtCsJEJRcBoVCjc+pnjnUihyu4RvO0HH722gZjM0btxc9zPFstA6dhbW767WaNxexC3W2jay1TuTWOO9VK/M4JWf3hWmWgbJt9u7J6WU2CslKhe3X7rqoCNdD3+XGthW7Byd1gj3HGACMLVnU+7OUGMoj6QEVO38M7QoDxbPncDdw8z2kjl8jnpujsrsTTQrQXLoOF2n3kN6Lqu3PkX6PrXluySHTxLrHqEyN4FdyT90jj6MVDe1xSmcehDN1iyuUJj4BYqqMfyVv4bXqrPwyffui0hQ5Hf9TVDRDTKHztIsLpO/+QnSc4n1jpIcPoEQCrPv/1t810YoKvHecXrOfg0QFO9cxqkW0WMpEoPH6D7zS0igMnN9nRBnj7xOq1KgtjhFq5xDj6bIHH6N3nO/QrO4RD03u6fVLl4adnAJqx98ROPq9XU/U0wToW8dhfcozbvL1G8tkNqkU3vs9DClj27SeFqBU4Iq+tHD7SvoS8ejOZOnMdnedfp8sjt/I4XWLCPy7EM1IcVaVRENX+5GldjtoQqNuJ5FUx7sz0opKbbm8fZxHgeZ51bg8H2qi1Msnf8B0ndBKLTKOfre+CaJ/sNU5idwqkUauTka+TliPWOY6e51ApfoP4JmxqjMT+A2A1eMXc5hl3MIRUV6Dp7doDJ/C99uX8JHIHCbVWbf/y5uI4jUqi5OoUdTmNlejFQnjfw8eixFcuQkSsRk6bM/Y3XyQiBMQtBcXaTntV8hNXKKZmEBu/Ig5FioGvlrH1C8c3mdC7P7zFewOgZpri7dd6GG7A+PihsEOXG1Tz7d8bla8wUaE/Mkzo61DVO3DvViDHbQnFp+qoLHQtdIvXN804Rmd7VK7fM7W7r0XlZKrUXqTpFkJGgOK4TAUOOkI70UWvu3Z5mK9BLVUigPpQS0vBpFezEUuDWeW4Fz6mXqKzOBuAFIn+bqIo3CApFEFiPRcX8/rr48TaL/CFbnALWlKTy7iWpEiXUP4zZrNPLzSHfzDejN8F2byuzEfXED8OwGzdUlEgNH0MygDUkknibaGQhSdWHygdUlJbWluzQL80Q7BjCSnesErp6bpVFYWCdujcICvtNCjyW3tTH+MiA0NWgNFNGCVkC6FgQO3GuNoygIVYCiBPst9/5Vg3+1THzDvm/tBxQYYyO0Ju+sja+h9/Zgz25eoeRR/KZDY3KZ1sIq1ujGHbXVqEHs2CC1y9M4W4S7b4YWN0lu0jlA+n7QmPXyAct9UwSqFUEYerC+kXtrG6zvw+sqFAXUtX/XvlfjJkbf7qRbeNJhtnqF45ksCtpaA1KVocQrlOylx/LS9gJdMemNHVnnGpVSslS/RcMtE4ZSBjy3Aud7Dl5rvbvGsxt4zRpmqgs18qDGX23pDs3iEvGeMcoz12nkZol1DxNJdlKevYFTf/IbBgT7cq3KI727pMT3HISioKjBZVZ0E81KUM/N4jbXByi4zSpus45mJVCN9fUJnVoJ31mfnyU9Bykliqa/lFGeQlPRUlG0dAw1YaEmLLSEhZaKoSZM1JiJGo2gGHpwM9Q1FE0Nboqasvbv49+zg954QlVJfuk9VtYETolaJN77Ivl/+W92/H6ad5dp3FrAHO5qG6oeOz1M5KdXnlzgFBHk1fW2b6bqN2watxexF1efbIzdQAQdxrV0DC0ZDdY3bgbfJ6KoMQMlZqA8KnaPrKeiqQh9TQA1dVe7pC/Ub9AdPUSnGUSiCiHotEbpix1joXZjT0VOVwx6o0foNEfQlQcFJmpOgfnaDVz/+a06s9s8twK3EUFXXz+44T90029V8tRzM2SPvIGZ6aG5ukSsdxxFi1BbnHpMKJ9g4McEaEPuzWuDTr33uv0+OncILEQpN4/uexkQuorelcLoyxDpSWMOdhDpzxLpSaNnEyjRjRto7gVqMokxNoyWTRM9dxYIgkye9MHZzpVo3F4k+eYRtNTG5b7u5cQ1bi/iN3d+AxWaSvrLJzeNFHQKVSqfTe6/ASBAzyaC9exOYQ51Ytxb264katw6UI15Xb/F7eLHGB0xEnonQgg0EWE89RYChZXGJE1v92uoWmqS7ughhhJnsLQHqSMtr8bdykWqTj5MEXiI51bgFFVfZ6VBEOyh6Ca+07ofiQiAlFQXJkkOBcEmrXKeaGc/rXKOVmllXUDHk7P1h8p3WnitOmrERDOi9/f9ADTDQjUsvFYD335ELOW2Tv/ColgRzNFuouO9WEf7iR7uI9KXQdlG1Ym9QpgGWlcXQteJ9K8FbPiS2qUnbJPiSRqTizTvLhM/M7rhIYquEjs9TOXCFPb8zstC6R2JtueGINLQXlilfnNnLtanQagKxmBQ8Nk62k/sWD/mSHdglR1wz0TRnud26WPGU2+uVfUXmGqcw6m3iOtZ8s0Zak6Bpld5qj0xTUQwtQRxPUvWHKLbGsNQ4/evT8utMVu7zFJ9Iuwg8AjPrcBpZgwz20tl7uaaQAmMRAdmugu7uopdK647vpGfp5Gfx+oYIO256LE0q7c+ux89+SjS9/FdBzVi7lpdN6dWopGfw0h1YXUOUpm9SaBcAjPbh5nqolVcwq4+Q/fQQUJTsEZ7SJwdI/7aGLFjAyib9C3bT9zlFco//HNks0XlXvPTp4xkbU7naEwuET0x2Fa8YycGMXrTgQtxJzlxiiDx+jhasn0xaLfSpHp5ettNP5+WSF+G+CsjJM4dIn5mFDVhHXhRe5Sl+gRS+gwnXqHDGgkCTrQYQ4kzdFmjFO1FqnaehlfB8Rq4fgtXOvjSQ+Lf9+Tci8ZUhIoqNFShoykRImoUS00Q1ztIGT0YanxdUEndLTFfvcZs9QqedNEVC0Uoj/Wq2ym+9LD9Z1OdZTd5bgVOiZgk+g/jNmvY5TyKbpAeO4NqRKndvoBdWS9wvtOitjRFrHuY1NBxfN+jvjKD12r3xyyp5+dJDh4lPX6WZn4eCCIaN0z03gZ2rUh55jrd6R46jr2Fqpu4zSqaGSM1+gpqxKJw67N1ASYvK2rMIPmFI6S+fIrEmdFtFcHdd3yf+oVLu5ai4VUa1G8vkMxVMPo23ie7lxNXvzm/IyESukr6Syfbvi6lxF2tUDl/e8fz3ilizRJNf+kkybeOoiUf74x90FGFRkSJElGjgKTulOiwgodVAEUoRPU0UT2NjPrYfpOWV8P2Griyhee7SLwHWxVCIFBQhbombgYR1cJQo2jCaHt9HD/4DPTFjt0XRlW5V4vyya9pzV3lTvmzJ/79g8JzK3BuvYJTr5AeexUhFNSIgVBVSlOXKE9fXRdxeI/q4hTpsTMkh05QnLq4JiTtb06Fmx+jmVE6T7yD26ggfR/PbjyxwEnXoTI3gWpESY+cpvvMV/A9F2Ut2bsw8Snl6Wsvfci/lo7R8c3XyPyFVzcNiNgM6fv4TQe/YeM1baTtIh0P6d778pHeQ//teqgxk+jJwbZNSB9DCLTebqJ9rwZFen2Jm89T//zKE80ZoHF7kebUUvC+N7g/CSGInx3bdvfpe5iDnUSPbJL71nJpTC3Tmt7bosGKqZN69wQdv3oOa7wPRd95WxcpJdJ28eqtYI1bztrauvfXUnr+urVWIhrmoZ4n/jw9ymjiHJaewlTjmGo8qODfxmoSQsFQoxjq9lop7YS43kEi1YlA2dWHhEJzNhS4Z4nTrFCcvIjQNMxkFwiBXSlQW7rT1sXnVIs49TK+564ld28ejVaZm0B6DmZ2AM2wkL6/zqUpfZ/Kwm0816FVXh9F6bs21flbuPUyzdLK/Z+7jQqrE5/SXF3CyvahRgw8p0VzNUjY9h7al7PLefI3PsKuFPCc9TezVjnPypWf0VxdxH+KFIeDhho36fyLX6DzW69vWkrqYaTv49Va2EtFnFwZt1jDLdfxqk28Wgu/aeO3XKTzqMgFX74T3ATNkU76+zLbFzhVJf72F3BX8ljHjtCankHv6nwqgbMXijQml4i/OoYa27gFU3S8j0h/ltZcHuluI/hIQOrdEyiR9lawW6lT+fT2lqXKngaha6S/cpqu33wboy/TtjTZw0gp8VsOznIJe7kUrG2pFqxttYnXdJAtJyjF5bjrHlik691fb60jQfdvvr1rAjeSfI2Ius3PyR4SNjbdnOf26gTJ1TXqK9Nso4cyAJoVQzWitMorNAqLW1tK0qe6MBnkrG34skd1/taGFp3v2lTmblKZu/nYa4EVOEF1fmLT4VvlPK2r72/4ml3Js/L5n28+/+cNVSH79bN0fvsN1OjW/fW8pk3z7gqNWwu0ZvPYi6vYK4HAedXG9m7+D6Glozu6wQsBajxG4d98FzUWpfznPyX11S/vaMxHkY5L/dYCrYVC22ojatwkfnKI+vXZbdWKVKzNOwdIz8deKVG9fPeJ570dkl84TOdvvLktcZO+DOp03pynOb2CvbAaCNxqFbdcRzo7DAxTFPwwcf2l47kVOGDHLuZY7yGsTC/lmeu0ys9/j6sXjdjxQbp+4wtbipt0PZpzBcofXKd6ZYbmnWXcYnXfI02lBK9cCVxDmoZ18jhK9Omf6huTizTvLGON9bQVgvjZMVZ/fHlbAhc7NoDR3z7J2W/Y1K7O4hZ2P6z9HsZQJx3fPIfRn91U3KSUuKU6pZ9dpXrpbpCTt1wKS9GFPBHPt8Btg6BocgbNjJEeP4e3Zlk9HKIf8uwRmkrXb76N3rl50Vq/5VC7Pkf+e59SvTi1bxF/G+J51D75FOk6NK5dD9yTV6499Wnd1RqNW4skXjvUtgBzkBPXRXM2h2xtbpmkv3SqfQK7BLfSoPzx5t6Ep0IRZL5yGmu8d8vUDnu+wMoffkLp/WsvTCeDkGfHCy9wsb5DZA+fQ9EMPLtB/vpHa8WJw8Tpg4R1pI/42dFNj5GuR2NykaV/9VNqV2Zgt/eLFGVnVWGkxC2XMY8dRdH1tT2fXdgPlZL6zTmas7m2AqdENOKvjlG9dBen1X4vWY2bxF9r323ed11a0ys0by8+9bTbYQx0EH91ZMsyaE6xyuL/9xNK799AOrvsTlTYUZWarZirXUMTBzCyd5eoOS9GqtJzJ3Buq0Zh4heoEWtb4fRBvUoPpMSurNIozD995ZKQXSf97olNUwGklDiFKrk//gW1z6f3xGWlaOrOqmWoKskvvYs9Mws+yEZz1+qCNmdyNKeWiR0fbHtd4q+MoHckcPLltu7Z2Kkh9Ey8bYSdX29R/mwSv7V3gUrx08PonalNr430Jbk/+gWl96/vfH9tGwT1KnevVNfd8mc8TRj+QedFabfz3Amc77R2FKbfyM2u68cWcjBJbGJlwFrwxc15yp9M7Nl+jBozdnYTFAKhR4KefmtNdp+m0v/D+A2b+sQ8iTfGMQc7NzxG70xgHe6jOb2C39g4YCr1xeNtLRcpJU6xTuUXT5b2sl2sI/1oyc33JlvzeVZ/eGlPxA0I6lbuYi7lXpThCtl9wjL0Ic8cNWGh92zeCdurtahemMSv712OoJaJIyLbf+YTBAWWhWmgWCaKZSLMraM/t0v9xhytmfxjdUvvj68oJF4bQ01sLB5q3CT+ykhbt6tsOdSvzwZBHHuEEjWIdCW3vK7ljydwi3u356bGzG2nnYS8ODx3FlzIi0ekOxW0Pdlk/8uv29Rvzu/pPIz+7I5KgUlAOg5euYxfX7PgWrsnwM5KmcbkIrFTw20toOiJocBNuVJ+zLKNnRpGS8faXlevblP68AaoCnpXJ2o6BVLiFUsosShuLg8IlHgMr1RG7+kKLFRFQYla+JUqXrmMEo3iN5p4q8XHxtDSMRRz6yLYtcvTe5qDp2XiaJn4np0/5GASWnAhz5ygVNPmx/iui52rbH7QU6CYEczhTlRrB7UupcSvVNDSafTubvTubrSO3ek5BkF+Wu3a7Kata7SkRez4AIr1uPst9dbRti5X6fm0FlepXZ1BMQz0vh78RpPI0ADGkUNoXZ1o3V0I00BNJ1HjMZRoFKFrGKNDCF1DGAZqIoESi6LENq7SoUYjiG1UK9nLVAChaxi9GfRsKHAvG6EFF/LM2c4NEE/i1fYuJcA63IvetXkgxGP4PpUPP1n3I+nubvRf49YCzdkc1qGeDbtwCyFInD1E8WfX1rlv1ZhJ7PRI2x5ofsuhen4Sv9ZCiUURkQhqMrHWzil4b9L10LIZtGwWPB81lUCo6pqw18D3UGIWyprIubk8srm+E4bQ1G1FprqVxp7lMUZ605gjXc+0+0TIsyFc8ZBnzrZcUyKIhNsTN5YiSH7hCJHO5M4C46TEWdi78HoAr9qkfmOe+OkRIt2pDY+JHh9AzyZwcpX7VlDs5BBaOrpWdPfRaUu8eovi+9cB8JstmjcmQCg484v3RdpvtlAiOm4ujxKN4lVq2NOzME0gZBLQVISeB+lvGNovPbkty0xoe+RMEhA93Ev0WP+LHPQY0oZQ4EKeOV61iZSb33+EqqAlozi5p+u+vhGxk0PEXxlBiR6MVjyPUrsyjf3u8bYCp0YNoscGaN5dwW8GVlzizcOBZbzBRZWuT2NigdbcWv1Uz8Nb3TjQxGsGVrMSreOVynjFnQWk+E17WyXTtHQMZ/nxfcSnxRjoIHFuvG0+YciLTbgHF/LMCURr8xubYuqYo127PrbWkSD7jdcwhzp3LYdtt2nN5WncWcZrkwqAEMTPjKCs7R8KUyf+ykjgTtwAaTuU3r8OO6jV6TeaeKWdP1y4pRrS3jrHLnq4D6Huromlxk2Sbx8jcW687bUIebE5mH/RIS8VTrGGW6q3DYcHUGMWibOHdnVcNWnR9RtfIHnuEOIg9ptbQzoetSszOCvtrafYiaH7lUJixwbQ0rGNrTcpcYo1yp/uMPdNbs/V+ChetRmI3Bb5gam3j++qCClmhNQXj9Px9bOoW+Tg7R8CXbGI6x1kjAG6rDF6ouP0Ro/QYx2myxojawyS0DuJbNJ+J2T7hC7KkGeP51O/Ob9pxXvF0omfGcE60kdjYuGph4wMZOn6tTdJvXcCNXHwG27Wrk5jLxYxhjo3nKuasLBGu7EXV0m8dgglom14nHQ8Kp9N4pUb+zFt8CXNmTzxMy20VPt+aNETA/f73D2tm1JLx8h89TQdv3qOSG/6ma2tgkoi0kXK6CUZ6cTSUmjCQBHqg67bIuiMIpEE//OR0sfHw/VtGm6JipOn1FqiYq/gype7V+ROea4FTs2miL5xGvPEOEoy9tgTYOUHH1D76af3v9cHe4m+cRpjfAjFNHALReqfXaXx+U1k/RkW7Q2h/NFNUm8fa7sRJxQFY6CDnr/6HvP/z59hLz6ec7UtNIXE2UN0fvsNYicHUaLtuyUfJNxinfrNOaJH+wPr7BGEIogeH6BycYr4mdG2kanScSn+5Mn71T0JtaszpN87uanAqWaEvr/zyziFypM/wCgCc6Sbzl97Y61TuPVM3M6WmqQndoROawRLTaApEVQRQRUqQmx/PlL6pCI9dEoHz7dpelUKzVkW67eoOQUkYT3drXhuBU7r6ST5rS9jjA3SvHUH7/Y0xtgg5qnDOPPL1D64QGviQX8r8+Q4yW9+Ga0ni7uYw10poPV0kP7ON9D7uqj84MMg9DnkmVD5ZAK3WEXPtg8GEBGNxGtjDP6Db5H7w4+pnJ/cds83xYwQOzVE+iuniZ0YRO9IoDxSXcNvOfgtN8jd2iAk/5kiJdVLd4Mb9wYCBxA90k/0SH8QULGR9eb79/vn7Sf1G3O05vMY/ZlNr6vRn2X4v/2LrPzbj1j90efIbfZvE5qKOdpN+iunSZw7RKQ79Vg+o+94+C0HRVd3tWTXw0QUi+HEGXqiRzDUGJpioOxA0B5FCAVVKKjooEaxtCQJvZPe2FFW6lPM1q6sFUUOWwm14/kUOCHQB7qxTh+h/ukVSn/0I6Tr0ujMkrQd9O4szuIK7nIQJaZmksTeOYfWlaH8vZ8EFpvroURNUr/+S8S/9Ab2zCKNizdgl/OYQraHW2mS/w+f0fvXv9L2GCEEGDqx0yMYgx00765QvXiHxtQS9lIRv97Cdz0UQ0eNmWhJC6O/A+tIH9ZYD5GuFGrCRGzgvpOez8offoz0fDq+/tqBTAq+19jVHO3eMKfLHOkKgk0MfWP3pOtT+vm1Pav32A6/YVP82bVgDTYpySYUgTHQQd/f/CrZr5+l8ultGrcXac0V8GoN/JaL0FW0mIkaN9G700SP9GGN92L0ZVATVlA15ZHam9L3KX8yQf3GHOl3TxA92r/L71DQYQ5xJP1FYnoGTeyNV0AIBV010RQDMxGjwxzkTuUCS/XbeKHrckOeS4ETmoqaSiB9iTO/fN/ychdXcJfyREYHUEwT/ODJJjI2RGSkn+a12zQuT+AVgs16v1yl9tNPiYwOEj13EntyBm9198PQQ7aBlOS+9xmpd09gjXa3PUwIgdBV9M4kWiZO9PgA0vaCIAYpkVIGNxdFIBQFoavBfpSuBe6qje47EvJ/eoHCn15AS0ZJv3viQAqcb7tUL08TOzm0oVAoUYPs11/bMN1BSonfdFj9+dP3q3sSSh/eIHHuEOlUdNNyaEII1FSUaNLCHOzAt91gbf2H1laIIOJSDdZWiWjB9kSbta1eukvu332EW6pjHe7ddYEbjJ/mcPotDCW6IxfkkyKEQBMGiUgXxzJfwtKSzFQuYfv7tK/6HPFcCpz0fPxmK7h5RR8UUBVGBMUykM7/3959xVie3Qd+/55/vPneyrGrc0/PTPfkxBlSQ4qkNKKwsihLq5UXa6xg2LJhG8a+2H6w/eAHw4BtrG1gbXnXwMJa7WJlWRIlUYmUKFKThxM793So0JXTzfd//+kcP/xrurumUofq6qrq8xkQM7i84V/h1u+ec34hWjWXy+rpwCzmCGcXkNXV7Z6CyVmk5+EcGNjWRrna3YtrTab+z7/g0H/797Fym2e+CSEQlomxxf22oqRk+Qefsvi99wnmKoRLdaK6h5Lq7kbn7JDGZ6N0fOP0ugFOCLHxzDWpqH96nWjp4XTBV+2Q+d97G3egg8yJoU2nNnwRxJIGyffxmlLRODvG3O+9RevSFAhBOFdFxXLbRucM507zWOk1LNNdt6j+QRLCwDHTHC48j0AwXv+MUAe5VfZkgEPK5BxtdpHMS08hm23ChSVSJw6TfuZx2peuE4zfasxrOA6YJtLz16Qry6YHYYxRSm3rvCjtHihoXZ7mxv/6p4z8k1964N3fZRix9Ocfsfj9D5OkFaVQQYQ/vkD6cN/d9aXcIcFcFe/abHJ92bUfyDbaGlNSUvnbcw+s3+Od8KeXmfrnP+DAf/odUof7Huj7TcVJtujc771F68rMzeG4wVyFqNzE7r7/wu8Od5gTpVexjK2Dm1KSQLbxoipeVMWPPSIVImWIRGIIA1PYmMLGMdOkzQIZq4htpjc9xxMILMPhUOE52nGDmeZlYvXgZvvtNXszwAHBxDS1v3yT0q98m132W2sAACAASURBVI7f+A6y7ROXazTf+YTmO58QV25tNaooAqUwHDvpzXdbuyfhOmAayCC8uaWpPTwqiql/dI2x/+EPGP7PvoM70PFAXidYqLHwB+9QefMCUa216py+dXWGwssndmWAQyUrsfxzR9YNcOs/RBEuNah9cv0BX9yWF4J3bZaJ/+VPGPytnyP75AjGnfQhvUtR3aPy43MsfO99goXqqve1P1MmWKzed4CzhM0TXV/HNlIbT2uQERV/hoX2GMveDby4hlIStfJPIikPSOJj8jzii3+EQdrMU0oN0pM+RMkZwDbX/9BnGQ7Hii9TCxaoBfPoxJPEng1wRiaNc3gY6fks/G//Cn9sMvkEHsXwpVVatFwhrjUwuzowshlk7dY2jd3XlZQMzC4it3HUiXbvVBjTODvG9f/u39D3a6/R8Y1TiG1qlCv9kNoHV1j44/fxrs2um3DhXZ3ZcIDobtA8O0EwV8Ed6ryzNHgF1TfPr3lfPBRS0Z5cYOx//AO6v/M8Pb/0EmZxe+oQVRTTujLDwvfeo/7RNWR77UommC1vS7u3g/lnyFjrJ8zEKmKpPcFY7ROq/gxSya1T+teLRwpC2aYeLjHVOE/e7mE4f5re9BGcdQKda+YYzp3iauUdfR63Ys8GOLOQwxkZRLZ9woVllOdveF//6gTh9DzpZ07Svnyd9pnPk60ayyT7lWexukrU/+ZdZKO1g1+BtimpCGbKTP72X7L45x/R/QvPUXjlsU1rqTYTLtWpfXSN8o/O4l2bSXo2bvAhtz2+QFRv4ciOXXkOJ9sBzXPjpI/2Y9/JjDOlWP6bsw/+wu6UAtloM/8H71L+27N0fusZOr55Gqe3dE/f77jl0zg3QflHZ2l8ep245W+4GxPM1wjmq6g4vufOKQYWQ7knMVg7wzCSAdeqP2W89jESyXaspBSSWEkqwQy1pXnK2SmOFF8ka68OsEII+jPHuVH/TAe4FWKz9kg7dhFC3PVFiLRL7mvPU/qVn0NYFqBQUiGbLdqXRmn8zXv4V2/VwaVPn6D43W9jlvK0Px9FVhs4B4dwDg7S+ugclT/6a+Kleywe3qNSIz0c+e9/A7u7sOF9yj85x+T/8ZfIBziq5o4YAiPtkD0xSPbJEVIHe3H6S1ilHGbGAUOgQon0Q+KWT7RcJ5gr0x5boHlpCv/GIrG38R++NUxj3SkvSqrdsZX9RaboHcaDO60XfCiEAFOQOdxH9vRB0kf6cQY7sTvzmFkXwzKTxDI/JG4HROUGwXwFf3KJ1uVpvGuzK9vM6s7iiSHWDaRKAnLr71NP6ghP97yBKW6VYyiliFXI5+W3mGic5UFvEfamj3Gi9BWydueqIKuU4lL575hsnNsXZ3FKqfv6hLknV3DCdcg8f4rc116kfWmU4PqNJGvSNLH6ukidPIqZy1D5wx8SjE4C4J39nKhaJ//6S6ROn8DIpIgWylT+6Ic03/1UF3nvdlIhmz71T0apfzL64F8vlrvnFMMQK2nw9/5eF86DK1xXUibn2vf6YVkpiBStKzO0rs/fSj7Z6Mtd52WSD7n3J8nl2Pz7pOKYzvQwQhirAwuKBW+UicaZ+76OOzHvXSXvdDGSfxrXvLWrIYSgMzWok01W7MkA5xwYIP+tV/GvTbD8u3+y+mxBQP7nv0b+9RexB3puBjiAcGKG5X/1xw/hijXt3uVefYrSr3wDZ7D7YV/KulqfXaH8//41/rWp+36urn/48xTeeGXXTnaofv8t8j8prGqErJRCqpDrtQ939Fqmm5foTh3EMdKrgm3G7sQQu6wTz0OyO3+LtmBkU5iFLNFieZ2DcwEoMMSG04w1TdPuVdrKrSkLaIZl6sHCjl5H0oh5kVit7r6UMrM7UnC+F+zJFZwKI1QcY/V2YeQzKH9lKW4Y2EO9uMcPIest4qW7G86oaZq2FVOs7mWpUFSD+YdyLc2oQqQCLG5dkynsHS863632ZIAL55bwPrtM5rknMIt5wvEpFGB1lZI2XY5D7a/fwb828bAvdVNuSuA44PuKYOMk0Adrq3MdxUMtDta03efL7xlFED+cM/wo9lBqF5R/7FJ7MsDFSxVq3/8x0fwy6adOkHnhNAiI6038i9dpfXSe9tVxCHdv42TXFbzwssvzrzi8/7bP+289hAhnCISz+a+AiuWWwyq1nSfbAbLpJQkeO0jYFmY2vW11iVtRSiGbHnKTMqAHxUinknFKXzoPTBobry6yj9TD+VsjkWsGBUcqvK2Q/NG2JwMcQFypUf/BW9R/8NbDvpR7EseK0Wshbhq85sP5ZRSOtWk3DLVSOK8D3O7T+uQylT/6CdEOl7akTh6i9CtfJ3V0eEdeT/kh1e+/Te2H7+/I692u8MZXKL7xCmZ+dUNML6qTFqvP4RzjwbaV24i9zkgeP26g1C4uC9lBezbA7XXpjGDksMXgkEVleee7ZgjbxOkpbpqtpoKIuNneHXVf2ioqipFee8frE2U7gHgnfx8UKggfSh2mCqJ1SxIa4RIdTh9f5OgJBK75cKZP2EYGQ6z+M94Myki9bQns0SzK/SBfNOjuMTHMO6ot3XZG2iX7xIFN7xO3fKKKrg/UtNst+1MoFd+2NSgour2rSgd2goFJ3u7CMm71TFVKUfFndA3cCh3gHpLZqZjzZwIW5mLa3g6vkITA7sqTe+bwpneLa62ky/7dPr3tYGZy99wKSdN2s3J7inZ0q5+tEIKUmafg9OzodeSdHtJWcVXNWyTblP3pNaUDjyod4B4SIUDGiunJmLmZnd1OMPMpSq+eJH1w4zekUopwuUEwW8XM5LAKHZiZPMI0MVJp7EIHZjqLME3MVAa70IGVzSNMC7ejm/yxJzGzG7cA07S9KpIBU82LSG6t4gxhciB/escKrE1h0585Tsa69R5TSjHnXceLauhpAgl9BveQxDGMj8aMj+5scDNSDvnnjtL5xrOb3k8FEf7UMrIhyR19AsOykYGPv7yAnS/idvURNap4MxO43f3YhRL+0gLe9Bix30bF+hOktn9NNs7TlzlK0ekHkuGjfZljzLdGWWyPPdAzMFPY9KQP05M+vGp8TjuuM9W4QCgfct/YXUSv4HYjQyBsM+nGsl0EWB05Cl85Qf8/+vqWXeiDuQqN8xOgDIhjGtcvEbdbFE6cxsoVCJbnEZaNnS9huClaU+M0rp0n9vSZnbb/hdLjauU9vKiGUioZPCpcHuv4WhJ4HlBWpWOk6U0fWZkmcGtWYhi3maifoR4ubj2a5xGiV3C7kFXMkjnWD0IQlpvEDQ/pBcSev2Fm14ZMgV3K4fSXKLxwnM43nsXKpzd9iPRDWldmaJ4dx7QLSSArlDBsl9hrgZQI2yFYmieslzFSmZsrNmFaWJl8sq2ZzhI1qg8ni0bTHrDF9jjXaz/lSOEFMnYJIQQZq8jjHa9zo3GOJW+cdtwgiD0k976iM4WFbWRIW3m6UyMMZE+Stgo3+0+GcZuZ1mWmmxeJ5MPqGLE76QC3C9mdObp/+WUyxwfxZ8r4k4sEc1WChSpRuYH0AmQQJS3LIola6eSupEIIkuQOy8TMutgdWTKPDZF//iip4a2b9Sop8SeXqL5ziajSxOwpYLopUj1DhPUy9StnsfJF7EJn0uQkjojqFeJ2Mn8qSTDJAgIzncEwLaTcvcNDNe1+TDbOoVTMSP4ZCm5vknBi5TlafJmB7AmWvBvUgnm8uE4kA2IVIlWEvJmFeXOcN0IIBAaGMDGEiSlsbMMlbRUoOL10poZJW4VV53x+3GS2eYWx+seE0scSTjLp4D5bdUnkvgiWOsDtYmbGJXO0n8zR/pu3ySAibrSJ6x5x0yNuBagwRsVxMvPLEBiujZF2cPpKK7Vud/bLrpQiKjepvH2R+ifXk9tkjL80jzczfnP7MSgvcLOpNRDWbmVaynaLxrULcO3C9nwTNG0XMjCxDBfbSNGMqix64xTcHr4IVoYwyNld5OwupJIEskU7quHHLYK4TayCJMitvIcEAiEMTGFhCQfbSOFaWVJmHttwN2ye3IqqNMNlSu4AlnCwhINpWCv3v/cg14qqTDXO3/Pjdwsd4PYYw7EwOnPYndtbWKqUIq55VN68wPJff4YwDMzuAsIWSMPHyLuIrJnMSVMK6QW3mlzvYcKxMXLppP1UysFIOQjHTgrgTSM5B5UqWSXLZLWsggDZDlDt5N+y4aGCvf+90O7cYPYkGbtE2iqSsYrJluEGKQ2GMEiZOVIPoBi84PRQ7OxFrDNd/H4styd1gNP2ByUVUblB5c0LLH7/p0TLDez+DtyhbuKGh92fxexxQAhUGCH9kGihSjCz/LAv/e4JgZFLY3WXsDqLWD0l7N4OrJ4SZjGHkc/c7LWYJPqYqDiGKE62hMOIuOkhq02iWhNZaxAtVIiWqsTVJnG1QVSpox5C70Rt55zo+CqOuflZ9k748mQDbTUd4B5xMozwJxapvHWR8o/OEC7Vk9ubbfypRaQXYLg20g+TnpRKIYMIuYsbWa/LMrG6ijgjfbiHh3CPDOIc7Mcs5G5NkN6AMCywLUgnfTutruKq/z9pCNwmnFsimlnCvzFHOLVANF8mWiwjWzrYadrDoAPcI0pFMcFCjebFSWrvXaL+0XXkbVuOcd0jrieJI80zow/rMu+fIbC6SqQeGyF96iipxw9hdZe2DGp3QwiBmUtj5obh6DDZWBKVa/iXxqn/+GO8c9e27bU0TbtzOsDtQnHLpz22gN2Zx+7MYaTdO04U2cwXKw1/ukx7YoHm+Qnqn40Rzu/PwbBG2sU9foDsi0+Qfvp4Eti2s7ZwA8I0sLtLcFzSeOfMA389TdPWpwPcLhQu1Vn+4ae0Lk/h9Jewu/JYxczKKiGFkXIwUnaSLWmbYBjJisQQSWKjTGa4yXZI3A6I6x5RtUW4VCeYKeONzuFdm93XjZTNriLZ50+S++rTuEeGENbO9sVUUUw4u0T78909dFe7NwveGJaxf8+/GsHSw76EbaED3C6kgoj22DztsXkAjLSDVchglTKYhQxmxsVIO5gpB+FYCHMlwJlGEuDiGBnFyFaQTASoNomWGwTzVeLG/m/jY/V3kf/6c+Reewq7p2PrBzwAstXGO3cd2fAeyutrD9a16vv3XWu2m+2XZs06wO0B0gsIvIBgbmeHW+5F9kA3hZ97ieyrT2EV7y0tW8US6QcQRqhYJtuatrWSWWltmY6tlCKq1Gl9evmeXl/b/VqRfi/uBTrAafuG1V0i/43nyb32NGYhu/UDVsRNj3BumWi+TLxcI260kJ6PCiOIZbIFbJsI28LMZTALWYxiDruniNXTiZFyVj2fCkKC69OE04vb/SVqmnYXdIDT9gUjnyH78pPkXnvqjoKbUopobpn2lRsEo9MEUwtEixXiSj1J61frN/wUjoWZz2IUslhdReyeDqz+TpzBHuyRPqxiDtnwaH54MQmOmqY9NDrAaXufZZI6MUL+9WfX1KitJ6418c5do/XJ57Q/nyBarCbzi+6ACiKipSosVQlGpwEwizmsvk6coR6cA31gGrQvjd3PV6Rp2jbQAU7b8+y+TnKvPY093LvlfYPpBRpvnaH5wXnC2SWI7n9uV1xtEFcb+FdurHRCSenkEk3bBXSA0/Y0kXJInTxE+qmjSf/ITQQ35qj98AMa759HVhvbfzFKIWtNZG3/ll9o2l6yLwOcSKdwDgyClMT1BrLpJQkChTxYJsprI/0AM59LGuf6AUY2g2w0UWGE1duFrDcAgZFLbo8bLeyhfoKrYzgHhxGWSVypgWniHBigffn6ymO0nWT3dpJ98XHMXGbT+4XzZep/+xGNd88i660dujpN0x6m/TnRO44RKRfhOgjXxerpwurtxh4eQJgmVncHqSeOYw/344wMYXWWsAd6MTJpnMMHUEGIbPtYvV0I00T5AUQxzmAfCIEzMohsecl94xizo4gKdTf5nSZsC+fQAKkTI5veT7Z9mj+9QOO9czq4adojZF8GOBWESVAyDGStgdXbheE6EEVJc91UaqXzh4H0A5SUEEvMYgHDdTA7ihiZNIbrEleqxLUGRsrF6u7E6u7AyGcx8jmwTGSzBQqEtS8Xw7ua2ZEn/cRhjExq0/u1P79B8/3zxMu1HboyTdN2g337VzmcmUOYFiqKUHFMXG+gpESFIdFSGaQC00T5PsQx8XIFhAApEa6DbHn418dXAphC+j6tD88gW22UnzxHNL+ICkK885/reWAPgdVZJPXEoU3vE9ebeGeuEIzP7MxFaY8M18zix/q8dTfbtwFO1pLzMCObIRybJG40MTJplB8kQevLmptnvSk/IBifBAHtS1eJF2/NQotm5rb12rWtCdfGHuzesizAH5uhfXliXwxn1XYPx8jwZOc3aUZlFr1xyv40cgfbW3WlRsjZnauGrMZEzDY/J5T7vx3fndq3Ae4Lst1Geu0k4SQINyzgvWMKwpn57bk47Z4ZuQzO4eRMdSMqiglGZwgm9c9L216dqWG60iN0qCG6UyM0oypL7RsseWO0ogc/nSNjFRnMPoFr3kquUkjaUZ0lbwLJ/Ze/7Af7PsCt6iYht6mzxB0WBWsPjplN4x7o2/Q+0XKNYHJeT9fWtl1v+jACA9uwsOxusnYXBbsbS1iM1j564K/fCJcQQMpa3W+1N32Yqj9LIHUdJuzTJBNt/zPSLlZf16b3iRbKhHP7Y+yHtnsYwqDkDtycJiCEwBAGjpnZkdUbQC1YwIvrKLX6Q3tnagTLcDZ41KNn/6/g9gi3qx9hmsjAR1g2ZiqDigJiv01m4CBBdRlv7gaZgYO0F2dRMiLdP4I3M47bNYCZzhA1qrQXZkDt8x6IpoFRzGIWNq99i5aqRAu667u2vTJWCdtYnbmrlCKQHkvejR25hliFNMMykTuEbd66lrSVJ2UV8KIaivs8jtkH9ApulzAcl+zIcaxsATOdQUYBZjqLMC1kHBH7LVQcrdxmIsMAK51FGCZuVy/+0hxuV9+mZ1L7hbAtrFJ+8/M3qYir299VxO7M4Q52kDs1zD4eB6ZtouD2IYS5amySQlH154jUzm2HN8IlQrn69QxhUrC7MYReu4Bewe0eAsJaGWFZmG4alZIIw0KGCyAEZiqDXejA6egmbrcQponT0YNTryAMg9hrIqz9O2H4dsK2MLaYGKB8n7jeRG1Dr8nbxQ2P3JPDCENgFbP7eiq6tr6sVVoz7FQpSdmf2tHraIblNQEOIGt3YgiTWOnMYR3gdon2/DT+4myS5WncWpnIMCD2WxBLlIwpn/0AFQWoOKZ85l1k4BMszSFDn/qVM6hof0zi3YywTMz85tuT0guQre1Pl5ZBTO2TMQDSB7tp6AD3yElb+TVDbxWSqr+z5UJeXCdWwZrbU1YeQ+z/nZw7oQPcLqGicMMdc9m+lREVt+o3/ztqrvx3mPySx+1HI3NKmCZG2t30PioIUe21b/7toKIYGUQYtn77PIpSZmHVCk6hUEia4fImj9p+QdwikgFKqVUBN2XmV9XHPcr0O1TbewyxZWs0FUXJRO5tZhUz9P7SC9TPjtO4uLNbUtruYBkOyNtWcAqCqEW0zmrqwVKEso0kxrztT7ltptasMB9VOsxre48hEPbmWzAqVqgHMFE79nxkGGF35JC6O8ojyRRrz7qDdc7CdkKsojWlAqaw0BlQCR3gtD1HIGCL2W/33bFmo6eNJe2JRcy0rjV6VJnGlwOcWvcsbCdIFa0pBzCFtSYJ5lGlA5y25yilVneoWYcwBMLY/je5YVsYjkVrbGHbn1vbK778uyfWCXo7ZW0o0+dvt+jvhLb3KLV1tqhpJP/bZnZHDiWhcOrAtj+3tjfEam3pyZcLv3eKZTgIVm/XJ30odZE36CQTbS+SassEEuHYGM72byNG1Ra1j67hdea3/bm1vSGUPmnS3H7O9dACnHAQYvUHOSk3zsh+1OgVnLbnqCgibmxeEmG4DuIBnJO5w51kjvaTOdGfzA/UHjl+1Fj33Ctnd+/oddhGOsmY/NImpS9baxJPHlU6wGl7jgrjLVtwGRkXI7d5Mfi9kE0fhKB5YfKBJbLsWQIMy4AHcPa5m7Si6qoAJ4RAYNCZGt7R6yg6PThGek1JQDtqoNacEz6adIDT9hwVRsS1ZpJssgFhWZiFLEZme7eOZBgTN9qkD/bs+z/kd6vrdD/P/Zdfo//FoVs3ii/9e+W/hSn2bCZ7PZxf87tnCIOe9CF28osquP045toPcY1waUeHr+5mOsBpe44KQqKlGmzRZ9LqyGN2Frb1tcOlGpmjvRiuDVKv4G63dGaW6tUlZJx8X9yOFJm+HIZjkh3I43akEKagdLyLwa8epHisE2HtvT9BFX8OqeJVQU6sjNDp2qFVXNoq0pUawTHTq25XSlELFtdNhHkU7b3fLk0DZMsjWtx8FI7VU8Lu7djW17XyGTJH+pIib30Gt6nC4U66n+rHybv0vTBE8UgnVsomO5AHIXj6P3kZt/RwkjPuRyus0IrKa243hc3hwgtY4sHWSAoMBrKPkbM71py/RdKnFszpFdwKHeC0PUm22oTTi5vex+rtxB7s2dZAFHk+/kINI+Nu2U1Fu83Kz0BYBijI9GSxsg7GAyjl2Amzzc9RxKvO4gxh0OEOcqz0yrrdTraDwKA3c5TBzGO45tqJGkvtG4Ry+5uM71V787dLe+TF9Rbt0elNz+HMTArnYD9Wd2nbXtftLRAu1pBeQOHZQ9v2vHudMARW2sJK2dhZG8MxkUGM6Zg4BRe3I4VhmfQ80092sMDMOxM0p+uoPbrNO926TCDba8rNTMNmOHeKw4XncYzVpQT3yxQOPelDHCm+SNbpXPP/SxUz27qiA9xtdIDT9iTZ9AjGZ1DB5v0g3aNDuMeGt20VF1Va1M9N0rg0hT9b3Zbn3A+srEPv80PkR4p0PzVA8XAHzekabkeakW8fI92dRUYxzZk6qc7kNiXVng1wQdziRv0sCrnmQ5ZlOBwuvMCprm9RdPqwjdR9dBcRmMImY5U4VHiWxzu/TtHpXTuPDsVye4qqP4vU52836UJvbW+Simihgj86TfrkoQ3vZvd3k37yCO3L48TLtft+WTOXpvDsIYy0w9wffnDfz7dfhHWf6U+nmH5rfNXtl373U4QhkkC2Egeq15aTCos9Gty+MF7/lL7MMfLr1L+ZhkVP+ghFt5/51nXmW9dpRMtIFRHLCEm8UqumVrY5RfLPSsmBISxMYeGaGTpSwwxkjpN3Np7UHcZtJuqf4cd6PuHtdIDT9qxoqYp39hqp4yOIDc5yhCFIP30c//oUjTc/vb8ROoYgdaAryaBUStfB3QmVTHZYdVO8P75vkfS5XH6Tp7rfwF0nXV8IgWtmOZA/zWDucVphlXq4SDNYxourRDIgkiFSRQghMA0HS9i4ZpaM3UHe7iRnd6/JlPyyWIZMNs5R8adX2nRpX9ABTtuzZL2Ff3mCaKm6abak3VMi99WniRYqeBdHtywv2PgFFc1LU1iFNEbaSY5X9sffau0eLbUnuF79KUeLL65bk/YFU1jknS7yTheszQ25Z7EMmfdGmWycI5CPxsDju6HP4LQ9LZiap/XBeVS8edBKnTxI4dsv4R4ZQtzHJO645RM32gTzVR3cNAAm6p8xVvsEL6qvaeH1IIXSZ8Eb42r1PVqRPg9ej17BaXtaXK7T+vRz0k8fxznQt+H9hGGQef4kmAa1H7yPf+UGsnX32WYqklTeu7L5nUwTM58Gw9iWcz9td1NIRmsfEcQtRgrPkLU6MI0H96dVKUk7bjDfGmW8/gmtaPN60EeZDnDanuePzVD/u08o/fLrmNmNzyuEaZB9/iRWV5H6Tz6mff464XwZ1b7/YZXCtTGyacxiDqu3g9SxYVQQUv79H933c2u7n0Iy2bxAPVzgYP45im4fKSu/Ml17m15DSQLp0QiXmWleZq51VZcEbEEHOG3Pkw2P1seXcUb6yb78JIazeZGte2gAe+DbtC9P0ProIsH4LFGljmx4SM/ffJiqEAjHwkg5CNfByKQw8xns3k6cg324xw7gHOgHFK1PP9/eL1Tb5RTVYJ7zy39Nd/oQfZmjZK1OXDOLbabuKdgpJYlUSBC38KIqS+1J5lpXV7Yk9R75VnSA0/aFcHqR2t/8FLOUI/34IYS1+a+24TpknjpG+skjRHPL+KNTBJPzRPMV4paHCiKQMvkbYogkS9MwMFwHo5TF7ixidhSw+zuxh3oxc1/qCXg/2ZranhariLnWVRZao+SdHjrcQfJONykrhyVcTMPGFBaGMFfq477IVlJIJZNSAhURyYBAerTCCtVglrI/rcsA7pIOcNr+oBT+lUmqf/YOhm3hHh2+o2QSYRrYg93Yg903n0e2A6TnJ0FKSrAsDMcCe2XlJsTD70MpBMI0wdrZdmHCNHZ4CoAAw9jxrxO472kRkphqMEs1mEVg4JgZMlYhWdEZKSzDxRQmQhhJ1QkxsQwJpU8gW3hRnXZUJ1L3v4X+qNIBTts/4pj2+WtUgOJ3XsU9MYKRusvGt0JgpF2MtPtALnG72H2dZF9+krjR2tnXHejBLGxjnvsWhGngHhsi//qzO/aaX7jfjNvbKSR+3MCPG9vyfNqd2RMBLl1yGHymm6AZMf3ZInGgh/k9bE7WoudECSdrMX+5QnNhdxx2qzCmdfYq0g/If/NF0qeOYBVzD3/Ftc1Sxw+QOn7gYV/GAydsi9wrp8m9cvphX4q2B+36OjjDFPSe7ODb/83zvPIfPUFhYPunNGt3r+Ngnpd+8yTf/K+fY/Cprod9OavFkvbFMcp/8CNqP/yA9vUpZNt/2FeladoO2/0rOENgOQama2I6BqajR5TsBqad/CxMx8DYiaGVAtIll3xfmqXrtTtaxUczS1T//B38q5NknnuM1IkR7P6uZNvyAa3olFTIVptgco725fGtH6Bp2gOz6wOcDCULV6p89DuXaS77VKd0FtFuUJ5ocOHPxkgVPr0WCQAAEq9JREFUHOYurh3+uN3slMnIS70cfKWPt//ZOZqLd7Ylqjwf77Mr+KPTpI4Nkzp5EGekH7u/C7OzgGFb9xXslFIgFXGtQbxcI1yoEIzP0r4yQTA6c8/Pq2na/dv1AQ6gNtPivX9x8WFfhnYbr+xz4U93boXiZG0OfaWf3pOle1rFy1qT1seX8c5fx+7vxjnYjzPUg9lVxCrlMPIZjHQKI+0iHCvJFjTNpKFyLFGxRMUxKopRLT8pJWi1iRse0XKNaL5MOLtEOLNINL+9AT+YWqDxk48xdjC5426E0wvEle1JnvAujKKk3LVnpu2LY1u2hdN2jz0R4DTNzdv0n+5Chvf3x0X5IcH4DMH4TNJSq5jF6ixilnIYuTRGJoXh2gjLRJhmskKLZRLY4hgVRMimR1xvIRst4lqLaLm6eXH4fQpGpwlGpx/Y8+8mrQ8v0vpQf5jVtseuC3B2xuLpXz2K6a4912lXAybem6M8sf6nRTttUhzO0XkwT7Y7hZ22UAr8Rkh1ssH85QpeeXWywaFX++k5UWTxWo3JjxYIW+sX6A49283Qcz005j0u/OnYzduFIcj3p+k6UiTfn8bNOQgDQi+mMe+xeKVC+UZjw6YD6Q6H7mMlSgdypAo2IAjbEe1qQHWqSXmsTrserP94AaXhHF3HCuT7MjhpC6UUoRfTWmqzPF5n8crqJqx2xuLkGyMIQ3D+T0YxLIO+xzvoPFzAzVrIWNFcajN/sczyWH3VYzsO5jnwYg/pjlsp9GErYvzdOZaur99z0bQNHv/OQUzH4PIPbmCnTPpPdVIYyGLYBu1qwMLlCnMXl1G3xwgB2a4UA6c7yXan6DpapDScpV0LePY3jtGu3aoN8soBkx8vsLzBNWwojomXa7pfpKbtU7suwJm2wYGXekkXnSSJwTaw0xbZ7hTVqSaNuda6Ac5Omxx6bYAnfvEgHYfyZDpdDCMJklEQU5tuMvr2LBf+dGzVOV7n4TzP/cMTlMfrlMfqVFrrB89nf+M4x392iM9+/9rNACeM5PEv/uZJuo8WyfelMV3z5ryr5mKb6c8WufBn40x+uLDmOUsjOU6+cYBDXxmgOJTBdMxkOKRS+LWQymSDD3/nMjd+Oo+MVkc40zU58rUBjr4+SO/JEvm+DJabbN1FfhLgLv/gxpoA52YtnvkHR7Eci5kziwy/0MuJbw7TeTiPnbFAwfJojY//zZU1AS7T6TL8XA9dR4u4eZtMp0vQCGkueBsHOMfkqV87QqE/Q6vsM/xcDwde6CFdcrGzFpEXsXC5yvnvj3HpLyduBnLDEHSM5Dj1y0fIdqfIdqexXJN0yeGxnzuAvG2mWGWiQX2udfcBTtO0fW3XBbigFfH+/30BO20lmXqWQXE4x/P/6MSmj1MKMiWXVMFh5swS1akmQSNEmIKuIwUOvtLPM3//KI15j0t/MU7oJVtd4+/OcfIXRug92UHn4Ty12RYyXL3dVBzOMfRsNzJWXPzz1edOhmnQdahAbarJ6NsztCsBMlbketOMvNTLyTdGMEyDpWu1VatHK2Vy6NV+nv61YzQX2lz4/jiNBQ+EwM1ZFAayZDqTlZJaZ/fr+M8O8cK//xidh/LMnF1i/N05WmUfYUCq4NB5ME9jk0SMVMHm9HeP0PdkJ+WxGuPvzyFDiVt0MC2RXMuXLI3W+OTfXiVdcug6WuTxXxi5eY1bSZdcnvv3jhM0Qq7+7RStZR/TMRg41cmxbwyTH8xQnWoyc2Zp5eepqM97XP6rCRCC0kiOV3/rSZoLbT7615+v+l76jXBNINc0Tdt1AU6GkulPl1bd1n2syOnvHtm0RVDUjhl9e4al0Rq1mRaNBS8JVAIK/Unt3GM/P0LfEx2MvzdL6CUdIMoTdeYvVug6XODgK33MnF1es4159PXBm9mC85dvjaZQEpbHa7z1z87SXGhTmWwQtZPA6eZsKjcafPU/P03XsQKdh/NM3fa8bt6m83AeN29z/k/G+OBfXiJohAAYliDbnSbd4VKbbqLk6tVb6UCO0989TPfRApf+6gbn/3iU+csV/JXHu1mb4lCWxuLGAxDdgsPwCz2c+94o1348TX22hZQKJ2PhFhyCerjmMe1KwEwl+dk0l9qMvNR7xwHOsAzSRYef/stLTHwwT+Qn36fOI3mcvMPBl3t59teP3QpwEqqTTaqTTRAw8FQXr/7Wk7RrAVf/dpratM6m1TRtc7u+0Ptu1GZaTH60QG26eWsVppLb5y9V8GsBmc5UshW3QkaK0bdnaC37HH5tgGyXuyqQmo7BiW8NYVgGF78/vqb+KvYl4+/OsXi1ejO4QbKqmLuwTG26mWyxdqVWPy6QBM3kvK8wmKVjJIfpGDevqT7bYv5imXZ1bR+6Ay/00HEwT33O48z/d43JTxbx6+EX/VrxGyHzlyu0ljYublaxYnm0xrk/TrZsZaxAQdCMqM+0bgbL7TT27hzTZ5ZuBjeA5et1zn3vOkrCwVf6cPObTwLQNE27U7tuBXc/hCHI9abpOVGkOJQlVXSxUyaGbdB9rIiTszEskTTLvc3UJ4tUbjQYfr6H/lOdVCabN4NV/6lOOo8U8Co+199av67JyVr0Pd5Bx8Hk7M9OW5iOQaYrRa4nTeBFa4qh/UbI5EcLHHiuh5EXe8l0OMyeLzN7fpm588s0Frx1tyaBlRZZNqOfzFCdat4887sboRcxc3b55qpxJyxera4Kbl+Y+ngRpRRO3qY4lGP+0oOvq9PujNVVwCzm8K+vZHEKgXt0EGe4h2B8jmB6ERXFGK6NCmM9RUHbVfZNgHOyNgdf6ePEt4fpOJjHdAzCVkTUjpMzse4UprUS2L601dmuBtz4cJ7exzs4+voQo2/P3gxwj/3cAey0xaW/mKD5pS0/YQi6jxd5+leP0nOiSKroEHoxYSsijiR2ysJKmQTe2je9ihXTny3xzm+f58jPDDLyUi+nv1viyNcGWB6tM/XpItffnKY21UR9KX6lO1xM26A+5xGH95aeLiOJt7yz7av8erhuMG4t+6CS0qdMx+5ucrwvCIHVkcMs5YjLDaJaEzOXRrZ8zHyauN5CpBxUJLF6SrcyeE0Dq6tI5snDmB15wuklhGngDPVgD3QRVxr447PIxsZb45q2k/ZFgBMChp7p4sXfPElhIMPE+3OMvTtLa8knbEfISHH09UGe/KVDGz7H9TdnePwXDzL0bDfFwSytJZ90yWHkpV6EEFz4/viqzD2AVNHh1f/4SUZe6mXxapWP//UV6rMtglaEjCTFoSwv/uOTmO76hclBI2Tip/Msj9W4/uY0vY+VGHymm6Hnuhl4qovex0t8/LtXWPh89Uj6LwKeENzz6BKlWPP1PGjCFOterzBv3SilHuL4oJmFDPmvP4s/OoOwbVQsyT53gmBygdQTh2i8cw73YB/e5QmsrgJCCNqXk87+ViGDkXaJ60kNIAjsvg7c4R4CwyCYWQJ0gNN2h30R4NxiMm2g92SJsbdn+fB3LrNwpbpqtTBwunPT51geqzN3ocyJbw0z8lIfi1drHHixl2x3mvnLFRYuV1bVoglT0PNYkUOv9ePXAt77FxeYeH9+1YoqDmVSKLwJFSvqsx71WY+ZM0uMvj1L3xMdnP7uEY59Y4jyeIP6fIt25dZZXGupTRxIisNZrD3UmzPb5WJYxppzzEJ/BiGSb29jfmfHvzyaBM5QD3GtiTc7hrBNnKEelAIzl8IZ7sFIOUgvQPkh9lAPACqKiSoNosUK0g+JKnVUFBM3k24uwdQCcofH92jaZvZFkomTtkh3uBimoHKjweK12qrg5mStlULqjWeDyVBy/c1p2rWAo68P4uQsjr4+iJUyufxXEwSt1WdVwhDk+zKYtkHgRdz4cGFVcDNsg0J/hsLgnbdXCpoRi1eqXP6rG4y/N4eMFF1HCmuue+5CGb8RMvhUN52H8hjW7mxr9GWDT3Vjp9d+pjr0aj8YgtZim9r0On8gFTd/nsIU2Om9E9R3o7jpUf2rD5BNj9yLJ1GxRIYRVkeOYHyO1LEhwrkyRDHS829tGUiF9Hzilk/cbKPaAUQxyguS2+qtZBK6pu0S+yLAhe3oZrJEYSBDaehWUMl2pzj1y4c5+HLfzSzFjdz4YJ7aTIvOwwWGn+1h4HQXQTPk+psza7bzlFS0VurM7JTFwKlbK0QrZXLwlT6e/rWjuNn1swLz/WmO/MwAg890r84cFMk15/uTwu2gGa5Z8Ux8kGRtugWbV/7DJzj2jSFSJSfZ/hNJjdvgM10ceq1/y+/dThpZOSN1Cytfr0g6xDz17x5BCMHlH9xYNwkFIGpHtJbbpEsuB1/uw7Bv+1mKpOheuwMCrFIO91A/Vm8HZkceFYRE8xUM1yEq17H7OgkXqzgHesg8dRT3yCDpJw4inPV/l+N6C6szT/7VU9j9m++UaNpO2hdblH4tZO5COcmEfK6Hb/xXz1Ier2OYBoWBDKkOl+XxOmKLEfReJWDigzm6jhZ4+tePke1Jc/VHkzTmvTWtslSsWLxaZebsEn2Pd/Az/+Rp5i+VifyYXE+afH+GyI+ZeH+O/DqruExnipNvjNB5uEBruY1XCYjDGDuVdG3pPFygMddi4oN5WsurC7abi20+/H8u4WQt+k918mr3KZ6a8/CbIYYpsFMmqYLDwpUqY2/P3vf3FyDTlaL/yQ7y/VnstEnpQI7SgRx2xuLEtw9QHM4lCTZexOTHC1Qn19bvzZ5f4vR3D3PkqwM0F9tYKZOOkTxdRwvMnFnis9+/tuHre5WAqz+e5sm/d4hn/8Fxhp7twW+EmI6BV/a5+BfjzJ3X2ZdbUiCbbdqfTwIKGUTIdkDz0yvJ2Vq1SeXP3iWuNVFhROO9CwjbIlysJL044xjv4jjIWx+6oqUazY8/x3Ad4rreotR2j30R4GSsmPhgDuO3BY+9MULvYyV6HysRehHl8Qbn/ug65bE6L/7jk1s+15W/meKJXzxE/5MdGKbBpb+YIN5gVdFcbPN3//QMT/47hzjwQi/HvzlMFMQ05z3G359n7J0Zhp7p4YlfWhvgmgttZs+Xyfdn6D5exMnYCCOpgWsttxl7Z5arP5rixofz684+m/5siR//z59y9PVBRl7qo/dkCTtjISOFXw9ZHq8x9cni3X8zN1AaznLqlw/T90QnhimwXBM7bWGYgoOv9jP0bA8ylshY8eb/fpb6bIs4WB3gLv/lDdIll2M/O8Thrw1gpy1ay23O/uEoZ//o+qajkLyKz6f/9gqxH3PotX4OvdaHipPONzNnFteUfmgbk56PPzaTZCmtbD/G5TpxOWnN5o8mSSKy4eGvkxH5xf2+oMKIcGox2UHQOULaLiK2SoLYkYsQYtOL6D5W5O/9T6+CgL/7p59y7Sfr16PZGYtcT4pU0cW0BDJWtGsBjfkknb5jJA8i6ZARrpO6D8nZWd/JElbKAqWYu1Am2KABMyRnQrneNNmuFJZjoFTyR7e52KZd8cl0pcj3palONZN0+Nselyo4ZDpdnIyV9KEUSRZh1I7xKj7NpTaxv0kZwMoQ0GxXCidrYVgGSilkKPGbEc0FLykAv41pG/ScKGLYBpWJxqpr2oybtykN53ByWxdiL4/VaC22USop3/jV/+tnGDjVxff+i7eYPrNEtsvFzTsII2ks3Vxsr7tKXvPlmoJsZ4psT+rmWZ6MJO1aQH3W2/Bnqmna3qSUuq9PrntmBSfM5Nxrs3gctpIVG6zfMHnx6tb9CmUomTm7fMfXpWJFfaZFfWb9rZnGvJf88V7ncV7ZX9MW7K4o7vo54lAyew9beX49vO/BpsJICtzv9WtWsaKx4K3bJ1PTNO3Ldv/RvAAnY5HpdG9uv2mapmnaVnZVgEsVnVWdLIQBXYfzPPPrx7BTFs2lNsujeiSKpmmatrVds0VpmIJDr/Xzyn/wOH49JGhFGLZBridFrjdNbbbF2T+8jrdO82FN0zRN+7JdE+AU0K4FREFMaSSPlTIBRWvJ5/MfTnLxz8aZPrOks7Q0TdO0O7Krsigt1yRVdDAs42bhrozUzULuL0+11vYAAbneNJZj0lz0bg6a1TRN28r9ZlHuqgCnaZqmaV+43wC3q5JMNE3TNG276ACnaZqm7Us6wGmapmn7kg5wmqZp2r6kA5ymaZq2L+2KLEpN0zRN2256BadpmqbtSzrAaZqmafuSDnCapmnavqQDnKZpmrYv6QCnaZqm7Us6wGmapmn7kg5wmqZp2r6kA5ymaZq2L+kAp2mapu1LOsBpmqZp+5IOcJqmadq+pAOcpmmati/pAKdpmqbtSzrAaZqmafuSDnCapmnavqQDnKZpmrYv6QCnaZqm7Us6wGmapmn7kg5wmqZp2r6kA5ymaZq2L+kAp2mapu1LOsBpmqZp+5IOcJqmadq+9P8DB1CIbJMDf6gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(7,5))\n",
    "plt.imshow(wc, interpolation=\"bilinear\")\n",
    "plt.axis(\"off\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
